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Compressed Counting Meets Compressed Sensing
[article]
2013
arXiv
pre-print
Compressed sensing (sparse signal recovery) has been a popular and important research topic in recent years. By observing that natural signals are often nonnegative, we propose a new framework for nonnegative signal recovery using Compressed Counting (CC). CC is a technique built on maximally-skewed p-stable random projections originally developed for data stream computations. Our recovery procedure is computationally very efficient in that it requires only one linear scan of the coordinates.
arXiv:1310.1076v1
fatcat:h3zwjvimkzhs3a6hbwvmu2tuju